AWS Big Data — Overview

Amazon Web Services provides many ways for you to learn about how to run big data workloads in the cloud. For instance, you will find reference architectures, whitepapers, guides, self-paced labs, in-person training, videos, and more to help you learn how to build your big data solution on AWS.

What is Big Data?

The term “big data” describes a massive amount of structured, semi-structured, and unstructured data pulled from a diverse variety of sources. The data volume is so large that traditional techniques and databases can’t handle it.

What is AWS?

AWS stands for Amazon Web Services, a subsidiary of Amazon, that provides a wide selection of cloud computing services and products on demand.

Using a pay-as-you-go model, AWS includes developer tools, email, Internet of Things (IoT), mobile development, networking, remote computing, security, servers, and storage, to name a handful. AWS consists of two main products.

There’s EC2 (Amazon Elastic Compute Cloud), Amazon’s virtual machine service, and S3; a scalable data object storage system.

How Do AWS Big Data Solutions Work?

AWS offers numerous solutions to help you address your entire big data management cycle.

These tools and technologies make it possible and cost effective to collect, store, and analyze your data sets. The tools available support the big data cycle from collection to consumption.

AWS’ big data solutions support distributed processing frameworks/architecture, predictive analytics, machine learning, real-time analytics, and petabyte-scale data warehouses.

And, unlike on-premise approaches, there’s no need to procure, deploy, and manage hardware.

The Big Data Technology Fundamentals course is perfect for getting started in learning how to run big data applications in the AWS Cloud. The course covers the development of big data solutions using the Hadoop ecosystem, including MapReduce, HDFS, and the Pig and Hive programming frameworks.